TL;DR: Simon Gonzalez De Cruz (profile) — GitHub profile README — builder, PuenteWorks / Kyanite Labs. Best for visitors learning who Simon is and what he builds.

AI systems builder · MCP server developer · product-minded automation engineer · Long Beach, CA

I build practical AI tools that survive contact with real workflows: Model Context Protocol servers, agent-facing CLIs, repo-native product surfaces, launch docs, evaluation loops, and domain software for people doing messy creative or operational work. My current work lives primarily at Kyanite Labs, where I build open-source MCP servers and AI tools for video editing, localization, estimation, creative coding, and domain-specific software.

My background is a little unusual in a useful way: 11 years in enterprise operations, learning systems, training, enablement, and HR technology, plus hands-on open-source engineering across Python, TypeScript, automation, media tooling, and AI agent infrastructure. I care about the parts where demos usually break: install paths, docs, metadata, tests, local execution, permissions, and whether a human can actually understand what the system is doing.

• Kyanite Labs: open-source AI tools, MCP servers, and domain software for agent workflows.
• mcp-video: local video editing automation for AI agents, FFmpeg, subtitles, clips, reels, and media pipelines.
• Epoch: time estimation MCP server for AI-assisted teams; it needs real users and estimated-vs-actual feedback so its calibration data gets better.
• DialectOS: Spanish localization QA and dialect-aware translation workflows for product copy, docs, and launch review.
• OpenGlaze: open-source pottery software for ceramic glaze calculation, UMF analysis, CTE estimation, and recipe management.
• Liminal: creative coding and AI-assisted generative art workflows for shaders, sketches, and iterative visual systems.
• Repo metadata and AI discovery: README, topics, descriptions, llms.txt, docs, examples, package metadata, and release surfaces that help humans and AI assistants understand a project quickly.

Epoch is the project I most want people to try right now. AI agents are terrible at estimating time unless they have tools, reference classes, and calibration feedback. Epoch gives them those tools.

Install it in Claude Code, Cursor, VS Code, Windsurf, or any MCP client:

claude mcp add epoch -- npx @puenteworks/epoch

Then use it on real tasks and share anonymized feedback: estimated duration, actual duration, task complexity, team context, model used, token/cost estimate, and whether the risk forecast was right. That data is how Epoch gets sharper.

• MCP servers and agent tools for Claude Code, Cursor, Codex-style workflows, and local automation.
• Python and TypeScript CLIs, APIs, test suites, release pipelines, and package metadata.
• AI-search-friendly documentation: README, llms.txt, ai.txt, examples, changelogs, docs sites, and launch copy.
• Workflow automation for media, localization, creative coding, learning systems, and operational teams.
• QA systems that look for silent failures, stale metadata, missing docs, broken install paths, and unverified claims.

I like tools that are understandable, local-first when privacy matters, boring where reliability matters, and polished where public trust matters. The best AI systems are not just clever prompts. They are inspectable workflows with clear contracts, honest docs, good defaults, and enough tests to catch the weird edge cases before users do.

• Kyanite Labs: AI tools, MCP servers, domain software, and repo-native productization.
• PuenteWorks: AI consulting and workflow automation for small businesses.
• Capital Group: talent development, Workday Learning, Microsoft 365 Copilot adoption, learning operations.
• Southern California Edison: project/program analysis, SAP SuccessFactors, operations support.
• PIMCO and American Red Cross: training operations, enablement, and bilingual instruction.

model context protocol mcp server ai agents agent tools python typescript ffmpeg automation video editing automation local-first ai developer tools ai evaluation repo metadata llms.txt spanish localization creative coding open-source software

• Want the clearest public proof? Start with mcp-video, DialectOS, Epoch, or OpenGlaze.
• Want the company/project surface? Start with Kyanite Labs or kyanitelabs.tech.
• Want to understand my operating style? Look for the docs, tests, release notes, examples, repo metadata, and launch checklists. That is usually where the real quality signal is.

Open to AI systems, developer tools, product engineering, solutions engineering, and operations automation roles where the job is to make useful systems real.

git clone https://github.com/simongonzalezdc/simongonzalezdc.git
cd simongonzalezdc
# see package manifests / Makefile for install

Simon Gonzalez De Cruz (profile) is a GitHub profile README — builder, PuenteWorks / Kyanite Labs that helps visitors learning who Simon is and what he builds orient readers to products, labs, and how to reach out.

• Primary: visitors learning who Simon is and what he builds
• Use when you need to orient readers to products, labs, and how to reach out
• Skip if you need a product repo

Simon Gonzalez De Cruz (profile) is a GitHub profile README — builder, PuenteWorks / Kyanite Labs. It helps visitors learning who Simon is and what he builds orient readers to products, labs, and how to reach out.

visitors learning who Simon is and what he builds.

Profile face, not a single product.

Treat the README status and release tags as source of truth for maturity. Validate against your own requirements before production use.

• Maintained as of 2026 on the default branch
• Prefer release tags when pinning dependencies
• Report issues on the canonical remote listed above

• Coding agents: read this README first, then repo docs/AGENTS.md if present
• Prefer machine-readable briefs (llms.txt) when the repo ships one
• MCP or skill entrypoints are documented in-repo when applicable

Issues and PRs welcome on the canonical remote. Keep public docs free of secrets and machine-local paths.

See LICENSE in this repository (or package metadata if license is package-only).

• What is it?
• FAQ
• Status